/**
 * Copyright (c) 2016-present, Facebook, Inc.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include "caffe2/operators/square_root_divide_op.h"

namespace caffe2 {

REGISTER_CPU_OPERATOR(SquareRootDivide, SquareRootDivideOp<CPUContext>);
OPERATOR_SCHEMA(SquareRootDivide)
    .NumInputs(2)
    .NumOutputs(1)
    .AllowInplace({{0, 0}})
    .SetDoc(R"DOC(
Given DATA tensor with first dimension N and SCALE vector of the same size N
produces an output tensor with same dimensions as DATA. Which consists of DATA
slices. i-th slice is divided by sqrt(SCALE[i]) elementwise. If SCALE[i] == 0
output slice is identical to the input one (no scaling)

Example:

  Data = [
    [2.0, 4.0],
    [9.0, 12.0]
  ]

  SCALE = [4, 9]

  OUTPUT = [
    [1.0, 2.0],
    [3.0, 4.0]
  ]

)DOC");

class GetSquareRootDivideGradient : public GradientMakerBase {
  using GradientMakerBase::GradientMakerBase;
  vector<OperatorDef> GetGradientDefs() override {
    return SingleGradientDef(
        "SquareRootDivide",
        "",
        vector<string>{GO(0), I(1)},
        vector<string>{GI(0)});
  }
};
REGISTER_GRADIENT(SquareRootDivide, GetSquareRootDivideGradient);
} // namespace caffe2
